Diagnose a retention problem

To: Leo | From: Activation PM | Re: Why WAU is flat, and why I'd hold off on doubling paid

Bottom line: This isn't a summer dip. Retention has been deteriorating since early August, and new sign-ups and win-back emails are hiding it. Doubling paid now would mostly buy users who leave faster.

1. What's happening

WAU = new + returning + retained users, which reconciles exactly every week. Across weeks 1–13, WAU moved only +227 (51,891 → 52,118). That flatness is three movements netting out:

• New users: +1,813 (up 30%, as you said)
• Returning users: +1,662, nearly all from win-back
• Retained users (active last week and this week): −3,248

Retained users held near 44.5–45k through week 4, then stepped down from week 5 and kept sliding to 41.6k. Churn (last week's actives who didn't return) rose from about 14% of prior-week actives in weeks 2–4 to about 20% in weeks 11–13.

2. Why it isn't summer

Seasonality would hit all cohorts alike. It doesn't. Cohorts 1–4 (signed up July to late July) had week-4 retention of 33–34%. Cohorts 5 onward (from the week of 3 August, the first week of the shorter sign-up) drop to 24–25% and stay there, even though cohorts 2–4 went through the same weather. The break lines up with the week-5 release, which removed the goal-setting step.

The funnel math shows the change is a net loss. Per 100 visitors:

We're converting more visitors into accounts, but by week 8 each signup is about 20% less likely to still be active. We're getting more users who don't build the habit.

3. Win-back is flattering the numbers

Win-back adds about 1,600 returning users a week. Of users who came back through a win-back email, 12% were still active two weeks later. Of users who came back on their own, 41% were. At 1,600 a week, that's roughly 190 durable returners instead of about 650 if they'd come back organically. We're also giving away a free week of Premium. "Returning users" now looks like a health signal, but most of it is low-quality.

The week-9 paid social increase (+25%) isn't visible as a break in the new-user trend, so I can't yet say what paid is adding.

What I'd do instead

1. Hold the paid increase. Keep current spend. Revisit when cohort week-4 retention is back above 30%.

1. Restore the goal-setting step, or move it into the app after the first workout. Run it as a holdout (50/50, old flow vs new), and judge on week-4 and week-8 retention per signup, not completion. Using the cohort tables, bringing cohort retention back to about 30% at week 4 is worth roughly 3–4k weekly actives at steady state. That's about the size of the whole retained-user decline. This is my rough estimate and needs confirming with the holdout.

1. Find the churn in tenured users. Most of the 41k retained base isn't new. Segment weeks 4–13 churn by tenure, plan usage, workout type, and platform. Also check whether win-back returners churn quickly the following week, since they add to churn in the same weeks.

1. Rework win-back. Test a smaller, conditional offer, or a guided re-entry workout instead of a free Premium week. Measure two-week retention against a holdout. Keep it only if the incremental retained users justify the cost.

1. Change what we report. Show the WAU decomposition (new, returning, retained) and cohort retention by signup week every week. Stop counting returners as growth.

On the summer theory: it's testable. If we have last year's data for the same weeks, compare churn rates. If summer were the cause, we'd expect last year's churn to rise over these weeks too, and we'd expect older cohorts to show the same pattern as new ones. The data so far points to the week-5 change.

Ask: Can we set up the sign-up holdout this week and pull the tenure-level churn cut before any paid budget decision?

To: Leo — Fix the retention leak before doubling acquisition

Weekly actives are flat because rising acquisition and reactivation are offsetting worsening retention. Summer could contribute, but the clearest break in the data follows the week-5 onboarding change—not the later increase in paid spend.

What’s happening

1. We are replacing more users, not building a larger active base.

Weekly active users equal retained users + new users + returning users. Equivalently, weekly net growth equals new + returning − churned.

From week 1 to week 13: - New users rose 30%, from 6,034 to 7,847. - Returning users rose from 973 to 2,635. - Weekly churn rose 44%, from 7,116 to 10,279. - Retained users fell from 44,884 to 41,636.

The result: weekly actives moved just 0.4%, from 51,891 to 52,118. The share of the previous week’s actives retained fell from 86.3% to 80.2%. This is deterioration beneath a flat headline.

2. New users look better after one week, but substantially worse afterward.

Compare signup cohorts before and after the week-5 release:

Only the week-5 post-change cohort has an observed week-8 result. Blank cells are unobserved, not zero.

The week-4 decline is roughly nine percentage points, or 27% relative, and repeats across multiple mature post-change cohorts. Earlier cohorts flatten near 30% by weeks 7–8; the first mature post-change cohort flattens near 20%. That suggests a smaller durable habit-forming base, not merely delayed engagement.

3. Win-back is masking the problem, not fixing it.

Returning users jumped immediately after win-back emails began in week 6. Lifecycle attributes about 1,600 extra weekly returns to the campaign, but only 12% of email-returned users were active two weeks later, versus 41% of earlier organic returners.

Those populations are not comparable enough to establish a causal campaign effect. Nevertheless, most campaign returners are not sustaining activity. Repeated returns and lapses can support WAU without creating lasting growth.

Likely diagnosis—and what remains uncertain

In week 5, we removed goal-setting and weekly-frequency selection. Signup completion improved from 61% to 74%, but subsequent cohorts became much less durable.

The leading hypothesis is that we removed a commitment and planning step central to a fitness habit. Alternatively—or additionally—the easier funnel admitted more low-intent users, lowering average retention. Both could be happening.

Timing alone does not prove causality. We lack randomized evidence, acquisition-source breakdowns, and a prior-year seasonal comparison. Still, the abrupt cohort break starts before the week-9 paid-social increase and persists afterward. “It’s summer” is not a sufficient diagnosis. Also, new-cohort deterioration may not explain all aggregate churn; we should examine established users separately.

What we should do before spending more

1. Hold paid spend at its current level. Don’t double distribution into a deteriorating retention curve.

1. Test lightweight goal-setting immediately. Randomize new visitors between current onboarding and a short goal/frequency step that produces a concrete weekly plan. Measure week-4 retained users per onboarding entrant, not just signup completion or retention among completed signups. This captures the conversion–retention trade-off. Track first-workout completion and second-week adherence as early signals; Premium conversion and revenue as business guardrails.

1. Localize the leak. Segment equal-age cohorts by paid/organic source, campaign, onboarding exposure, and initial workout/plan behavior. Check existing-user retention around week 5. Reconcile the differing signup totals across the two exports before joining them.

1. Evaluate win-back with a randomized holdout. Optimize for incremental sustained activity and eventual revenue—not email-driven return visits alone.

Increase acquisition only after we demonstrate improved durable retention and acceptable channel economics. Right now, more acquisition would buy more arrivals; it has not demonstrated that it will buy lasting growth.

To: Leo, Head of Growth From: PM for Activation Subject: Diagnosis: Why WAU is flat and why we shouldn’t double paid acquisition yet

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Executive Summary

WAU is not flat because of summer seasonality. It is flat because of a structural collapse in early habit retention starting in Week 5, which is currently masked by two temporary factors: the Week 6 win-back email campaign and higher sign-up volume.

Our core retained user base has dropped by over 3,200 users, and weekly churn has surged by 44% (from ~7,100 to over 10,200). Doubling paid acquisition today would pour money into an onboarding funnel that currently retains a third fewer users long-term than it did two months ago.

Here is what the data shows and what we should do instead.

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1. The Evidence: The Week 5 Onboarding Change Broke Habit Retention

If summer outdoor seasonality were the culprit, we would expect a gradual, platform-wide decay across all cohorts. Instead, the cohort data reveals an immediate step-change break between Cohort 4 and Cohort 5:

• Cohorts 1–4 (Before Week 5): Week 4 retention was steady at 33.4%–34.2%, flattening to a healthy 30% at Week 8.
• Cohorts 5+ (After Week 5): Week 4 retention plummeted to 24.5%–25.0%, and Week 8 dropped to 19.9%.

This represents a ~33% relative drop in long-term cohort retention.

Why did this happen? In Week 5, we removed the goal-setting step ("What do you want to achieve, and how many days a week?") to cut sign-up time from 3 minutes to 1 minute. While sign-up completion jumped from 61% to 74% and bumped Week 1 retention slightly (55% to 58%), we stripped away the user’s commitment and personal investment.

Stride is a habit product. Without clear goals and a tailored weekly schedule, users drop off rapidly after Week 1 because they lack direction and accountability.

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2. The Illusion: Why Topline WAU Looks Flat

If retention collapsed by a third, why hasn't WAU cratered? Two factors created an artificial floor:

1. Top-of-Funnel Inflow: Sign-ups grew ~30% (boosted by higher sign-up completion and the Week 9 paid budget increase), adding ~1,800 gross new sign-ups per week.
2. The Week 6 Win-Back "Sugar Rush": The win-back campaign added ~1,600 returning users per week (jumping from ~1,000 to ~2,600 in growth accounting).

However, this resurrected volume is extremely low-quality: * Historically, 41% of organic returning users were still active two weeks later. * For win-back users, only 12% remain active after two weeks.

We are cycling low-intent, discount-incentivized users who churn almost immediately. Meanwhile, underlying retained users dropped from 45,074 (Week 3) to 41,636 (Week 13), while churn surged from 7,116 to 10,279 per week.

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3. What Happens If We Double Paid Acquisition Now?

Doubling paid acquisition right now will accelerate cash burn without growing the business:

• Impaired Unit Economics: With Week 8 retention down from 30% to 20%, LTV has dropped sharply. Premium conversion will suffer because fewer users build the 3-week habit required to see the value of paid features.
• Higher CAC for Diminishing Returns: Scaling paid spend when the conversion engine is degraded will cause CAC to rise while payback periods stretch unsustainably.
• A Leaky Bucket: In Week 13, we added 7,847 new users and churned 10,279. Adding more sign-ups does not fix a machine that is churning users faster than it can onboard them.

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4. Recommended Action Plan

Before increasing ad spend, we need to plug the leak and fix activation.

1. Reinstate and Optimize Goal-Setting (Immediate): * Re-introduce the goal-setting and schedule-commitment step in onboarding, framed as building the user's "Personalized Weekly Plan." * Test progressive onboarding: let users quickly select goals without friction, but ensure their first workout calendar is anchored before Day 1. * Target: Return Week 4 retention to ≥33%. 2. Re-evaluate Win-Back & Lifecycle Spend: * Stop relying on the 21-day "free Premium week" email to prop up WAU. Shift CRM focus to Days 1–7 activation, reinforcing the weekly plan set during onboarding. 3. Hold Paid Social at Current Levels: * Keep paid spend flat (or pull back the Week 9 25% increase) until Cohort Week 3/4 retention recovers. 4. Scale Acquisition Once Activation Is Fixed: * Once Cohort Week 4 retention crosses 32% for two consecutive cohorts, we double paid acquisition. At that point, every dollar spent will generate 50% more long-term active users than it would today.